CN115796776A - Intelligent after-sale service fusion system based on big data - Google Patents
Intelligent after-sale service fusion system based on big data Download PDFInfo
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- CN115796776A CN115796776A CN202211488667.1A CN202211488667A CN115796776A CN 115796776 A CN115796776 A CN 115796776A CN 202211488667 A CN202211488667 A CN 202211488667A CN 115796776 A CN115796776 A CN 115796776A
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Abstract
The invention discloses a big data-based intelligent after-sale service fusion system, which comprises the following modules: the system comprises a basic data module, a production management module, an inventory management module, a workshop product module, a working hour management module, a quality management module, a report analysis module, a financial management module and an after-sale service module, wherein a business database adopts a mode of combining the Internet and an enterprise intranet, and is used for managing cooperative office, human resources, customer relations, supply chains, logistics, after-sale services and the like, the sharing degree is high, management which mainly takes information data and does not have complex real-time calculation is preferentially constructed on the basis of the Internet, an important function module surrounding production management is a function module which has strong data correlation with the enterprise production and management, strong privacy, strong confidentiality and high correlation strength between the modules with complex calculation degrees, and the enterprise intranet is preferentially constructed to realize the digital management of the enterprise.
Description
Technical Field
The invention relates to the technical field of big data fusion, in particular to an intelligent after-sale service fusion system based on big data.
Background
Each enterprise has its own production mode, and the purchasing, production, processing, inspection, shipment and after-sale of raw materials are summarized in detail, each step contains a large number of details, the recorded contents of different categories are different, such as the purchasing of raw materials, and not only contains the purchasing place, purchasing amount, whether the raw materials are qualified or not, the purchasing place, purchasing quantity, warehousing mode and the like of the raw materials, and a plurality of items in each category are added, so that the enterprise manages the categories.
Disclosure of Invention
Technical problem to be solved
In order to overcome the defects in the prior art, the invention provides an intelligent after-sales service fusion system based on big data, which is used for solving the problems in the background art.
(II) technical scheme
In order to achieve the purpose, the invention provides the following technical scheme: the intelligent after-sale service fusion system based on the big data comprises the following modules:
(1) and a basic data module: browsing detailed project parameters of different materials through a browsing window;
(2) and a production management module: editing the items of the detailed parameters of different materials through an editing window;
(3) and the inventory management module: editing the detailed classification of the purchase receipt of different materials through an editing window;
(4) and a workshop product module: editing the order list of the outsourcing to the workshop of different materials through an editing window;
(5) and a man-hour management module: editing the work content of workers in different process operations after item classification through an editing window;
(6) and the quality management module: the detailed classification of different material production parameters is convenient and fast through an editing window;
(7) the report form analysis module: editing and counting the classification of different worker material requisites through an editing window;
(8) the financial management module: editing detailed categories of accounts of different materials through an editing window of the financial statement;
(9) and an after-sale service module: product quality and after-market service business tracking is presented by examining, analyzing, and qualifying workers' product quality in tabular and bar chart form.
Preferably, the material parameters in the production management module include a general figure number, a sub figure number, a classification label and a category of a auditor on the basis of the detailed material parameters of the basic data.
Preferably, the detailed classification of the different material purchasing receipt in the inventory management module comprises the following steps:
the receipt ID number of the receipt, the receipt type, the receipt number, the department name, the clerk, the receipt date, the accounting company, the sales order number, the purchase order number, the production order number, the product model number, the product lot number, the product number, the abstract, the material name, the specification model number, the unit, the real receipt number, the overflow number, the unit cost, the overflow cost, the income bin, the manager, the warehouse manager, the responsible person, the auditor and the system person.
Preferably, the worker work content item classification in the man-hour management module includes the following:
document ID number, process type, document number, department name, employee, document date, accounting company, job team, job status, production order number, customization, and abstract.
Preferably, the detailed classification of the production parameters of different materials in the quality management module comprises the following:
document ID number, document type, document model, document date, accounting company, order number, inspection mode, quality inspection department, abstract, material name, specification model, unit, process name, inspection category, inspection item, manufacturer, total number, sampling number, unqualified number, inspection result, processing method, repair number, waste number, product number, design value, allowable tolerance, result value and remark.
Preferably, the classification of different worker material requisites in the report analysis module includes the following:
material name, specification and model, unit, department, warehouse, staff, date of getting, document code, abstract, material quantity, total material quantity, material average price and total material amount.
Preferably, the different material account categories in the financial management module include the following:
subject code, subject name, beginning balance, debit, credit, direction of balance, and balance.
Preferably, the categories presented by the table and bar chart in the after-sales service module include the following:
worker name, total number, rejected number, rework number, scrap number, pass rate, rework rate, and scrap rate.
(III) advantageous effects
Compared with the prior art, the invention provides an intelligent after-sale service fusion system based on big data, which has the following beneficial effects:
aiming at production type enterprises with complex and various products, the storage, safety and controllability of enterprise data are considered; considering from hardware, software and manpower cost; considering from the aspects of operation maintenance, high efficiency, practicality, high efficiency operation and the like of a digital system, a business database adopts a mode of combining the Internet and an enterprise intranet, the management of cooperative office, human resources, customer relations, supply chains, logistics, after-sales service and the like is preferentially constructed on the basis of the Internet, the management which is high in sharing degree, mainly takes information data and does not have complex real-time calculation is preferentially constructed on the basis of the Internet, important function modules surrounding production management are strongly associated with data of enterprise production and management, the function modules are strong in privacy, strong in confidentiality and strong in association strength between the modules with complex calculation degree, and the enterprise intranet is preferentially constructed to realize the digital management of the enterprise.
Drawings
FIG. 1 is a block diagram of a fusion system of the present invention;
FIG. 2 is a block diagram of the basic data of the present invention;
FIG. 3 is a block diagram of the production management system of the present invention;
FIG. 4 is a diagram of an inventory management module of the present invention;
FIG. 5 is a block diagram of a shop product according to the invention;
FIG. 6 is a diagram of a module for managing working hours according to the present invention;
FIG. 7 is a diagram of a quality management module of the present invention;
FIG. 8 is a block diagram of a report analysis module of the present invention;
FIG. 9 is a diagram of a financial management module of the present invention;
FIG. 10 is a diagram of an after-market service module according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a technical scheme, and discloses a big data-based intelligent after-sale service fusion system, which comprises the following modules as shown in figures 1-10:
(1) and a basic data module: browsing detailed project parameters of different materials through a browsing window;
(2) and a production management module: editing the items of the detailed parameters of different materials through an editing window;
(3) and an inventory management module: editing the detailed classification of the purchase receipt of different materials through an editing window;
(4) and a workshop product module: editing the order list of the outsourcing to the workshop of different materials through an editing window;
(5) and a man-hour management module: editing the work content of workers in different process operations after item classification through an editing window;
(6) and a quality management module: the detailed classification of different material production parameters is convenient through an editing window;
(7) the report form analysis module: editing and counting the classification of different worker material requisites through an editing window;
(8) the financial management module: editing detailed categories of accounts of different materials through an editing window of the financial statement;
(9) and an after-sale service module: product quality and after-sales service business tracking is presented by examining, analyzing and assessing worker product quality in a tabular and bar chart manner.
Furthermore, the material parameters in the production management module include a general figure number, a sub figure number, a classification label and a category of an auditor on the basis of the detailed material parameters of the basic data.
Further, the detailed classification of the purchase receipt of different materials in the inventory management module includes the following:
the receipt ID number of the receipt, the receipt type, the receipt number, the department name, the clerk, the receipt date, the accounting company, the sales order number, the purchase order number, the production order number, the product model number, the product lot number, the product number, the abstract, the material name, the specification model number, the unit, the real receipt number, the overflow number, the unit cost, the overflow cost, the income bin, the manager, the warehouse manager, the responsible person, the auditor and the system person.
Further, the worker work content item classification in the man-hour management module comprises the following steps:
document ID number, process type, document number, department name, employee, document date, accounting company, job team, job status, production order number, customization, and abstract.
Further, the detailed classification of the production parameters of different materials in the quality management module includes the following:
document ID number, document type, document model, document date, accounting company, order number, inspection mode, quality inspection department, abstract, material name, specification model, unit, process name, inspection category, inspection item, manufacturer, total number, sampling number, unqualified number, inspection result, processing method, repair number, waste number, product number, design value, allowable tolerance, result value and remark.
Further, the classification of different worker material requisites in the report analysis module includes the following:
material name, specification and model, unit, department, warehouse, staff, date of getting, document code, abstract, material quantity, total material quantity, material average price and total material amount.
Further, the account classification of different materials in the financial management module comprises the following:
subject code, subject name, beginning balance, debit, credit, direction of balance, and balance.
Further, the categories presented by the table and bar chart in the after-sales service module include the following:
worker name, total number, rejected number, rework number, scrap number, pass rate, rework rate, and scrap rate.
The working principle of the device is as follows: when the basic data module is given to the fusion system, detailed project parameters of different materials can be browsed through a browsing window, the types of products produced by enterprises can be conveniently observed, and the fusion system is based on the production management module: editing the items of the detailed parameters of different materials through an editing window, wherein the material parameters in the production management module comprise a total figure number, a sub figure number, a classification label and the category of an auditor on the basis of the detailed parameters of the materials of basic data; based on the inventory management module: the detailed classification of the purchase receipt of different materials is edited through an editing window, and the detailed classification of the purchase receipt of different materials in the inventory management module comprises the following components: the bill ID number, the receiving type, the bill number, the department name, the salesman, the bill date, the accounting company, the sales order number, the purchase order number, the production order number, the product model number, the product batch number, the product number, the abstract, the material name, the specification model number, the unit, the actual receiving quantity, the overflow quantity, the unit cost, the overflow cost, the receiving bin position, the manager, the bin management, the responsible person, the auditor and the system person of the receiving order are provided for an observer to better observe the stock information; when based on workshop goods module: editing the order list of the outsourcing to the workshop of different materials through an editing window; based on the man-hour management module: the work content of workers in different working procedure operations is edited after project classification through an editing window, and the work content project classification of workers in the man-hour management module comprises the following steps: the ID number, the process type, the document number, the department name, the staff, the document date, the accounting company, the operation team, the operation state, the production order number, the self-definition and the abstract of the document enable the observation of the detailed content of each worker during working; based on the quality management module: the detailed classification of different material production parameters is convenient and fast through the editing window, and the detailed classification of different material production parameters in the quality management module comprises the following steps: the method comprises the following steps of counting ID number of documents, types of documents, dates of documents, accounting companies, order numbers, inspection modes, quality inspection departments, abstracts, material names, specification models, units, process names, inspection categories, inspection items, manufacturers, total numbers, sampling inspection numbers, unqualified numbers, inspection results, processing methods, repair numbers, waste product numbers, design values, allowable tolerances, result values and remarks, and an observer can conveniently observe whether products are qualified after production is finished; based on the report analysis module: the classification of different worker material receptions is compiled and counted through the compiling window, and the classification of different worker material receptions in the report analysis module comprises the following steps: the material name, specification model, unit, department, warehouse, staff, picking date, document code, abstract, material picking quantity, total material picking quantity, material picking average price and total material picking amount, so that an observer can observe the use condition of workers on the material conveniently; based on the financial management module: the detailed classification of different material accounts is edited through an editing window of the financial statement, and the classification of the different material accounts in the financial management module comprises the following steps: the account codes, the account names, the initial balance, the borrowers, the lenders, the balance directions and the balances facilitate observers to observe the details of accounts; based on the after-sales service module: product quality and after-sales service business tracking is presented by checking, analyzing and assessing worker product quality in a form of tables and bar charts, and the categories presented by the tables and bar charts in the after-sales service module include the following: the name of the worker, the total number of workers, the unqualified number of workers, the rework number of workers, the abandonment number of workers, the qualification rate, the rework rate and the abandonment rate of workers facilitate observers to observe real-time tracking information of after-sale service businesses.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (8)
1. Wisdom after-sales service fuses system based on big data, its characterized in that: the intelligent after-sale service fusion system based on big data comprises the following modules:
(1) and a basic data module: browsing detailed project parameters of different materials through a browsing window;
(2) and a production management module: editing the items of the detailed parameters of different materials through an editing window;
(3) and an inventory management module: editing the detailed classification of the purchase receipt of different materials through an editing window;
(4) and a workshop product module: editing the order list of the outsourcing to the workshop of different materials through an editing window;
(5) and a man-hour management module: editing the work content of workers in different process operations after item classification through an editing window;
(6) and a quality management module: the detailed classification of different material production parameters is convenient and fast through an editing window;
(7) the report form analysis module: editing and counting the classification of different worker material requisites through an editing window;
(8) the financial management module: editing detailed categories of accounts of different materials through an editing window of the financial statement;
(9) and an after-sale service module: product quality and after-sales service business tracking is presented by examining, analyzing and assessing worker product quality in a tabular and bar chart manner.
2. The big data based intelligent after-market service fusion system of claim 1, wherein: the material parameters in the production management module comprise a total figure number, a sub figure number, a classification label and the category of an auditor on the basis of the detailed material parameters of the basic data.
3. The big data based intelligent after-market service fusion system of claim 1, wherein: the detailed classification of the purchase receipt of different materials in the inventory management module comprises the following steps:
the receipt ID number of the receipt, the receipt type, the receipt number, the department name, the clerk, the receipt date, the accounting company, the sales order number, the purchase order number, the production order number, the product model number, the product lot number, the product number, the abstract, the material name, the specification model number, the unit, the real receipt number, the overflow number, the unit cost, the overflow cost, the income bin, the manager, the warehouse manager, the responsible person, the auditor and the system person.
4. The big data based intelligent after-market service fusion system of claim 1, wherein: the worker work content item classification in the man-hour management module comprises the following steps:
document ID number, process type, document number, department name, employee, document date, accounting company, job team, job status, production order number, customization, and abstract.
5. The big data based intelligent after-market service fusion system of claim 1, wherein: the detailed classification of different material production parameters in the quality management module comprises the following:
document ID number, document type, document model, document date, accounting company, order number, inspection mode, quality inspection department, abstract, material name, specification model, unit, process name, inspection category, inspection item, manufacturer, total number, sampling number, unqualified number, inspection result, processing method, repair number, waste number, product number, design value, allowable tolerance, result value and remark.
6. The big data based intelligent after-market service fusion system of claim 1, wherein: the classification of different worker material requisitions in the report analysis module comprises the following:
material name, specification and model, unit, department, warehouse, staff, date of getting, document code, abstract, material quantity, total material quantity, material average price and total material amount.
7. The big data based intelligent after-market service fusion system of claim 1, wherein: the different material account classifications in the financial management module include the following:
subject code, subject name, beginning balance, debit, credit, direction of balance, and balance.
8. The big data based intelligent after-market service fusion system of claim 1, wherein: the categories of the table and bar graph presentation in the after-market module include the following:
worker name, total number, rejected number, rework number, scrap number, pass rate, rework rate, and scrap rate.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117787816A (en) * | 2024-02-28 | 2024-03-29 | 山东中翰软件有限公司 | Material data quality detection method and system for industrial enterprises |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117787816A (en) * | 2024-02-28 | 2024-03-29 | 山东中翰软件有限公司 | Material data quality detection method and system for industrial enterprises |
| CN117787816B (en) * | 2024-02-28 | 2024-05-24 | 山东中翰软件有限公司 | Material data quality detection method and system for industrial enterprises |
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